BODIPY-Labeled Estrogens for Fluorescence Analysis of Environmental Microbial Degradation

Biodegradation of estrogen hormone micropollutants is a well-established approach toward their remediation. Fluorescently labeled substrates are used extensively for rapid, near-real-time analysis of biological processes and are a potential tool for studying biodegradation processes faster and more efficiently than conventional approaches. However, it is important to understand how the fluorescently tagged surrogates compare with the natural substrate in terms of chemical analysis and the intended application. We derivatized three natural estrogens with BODIPY fluorophores by azide–alkyne cycloaddition click reaction and developed an analytical workflow based on simple liquid–liquid extraction and HPLC-PDA analysis. The developed methods allow for concurrent analysis of both fluorescent and natural estrogens with comparable recovery, accuracy, and precision. We then evaluated the use of BODIPY-labeled estrogens as surrogate substrates for studying biodegradation using a model bacterium for estrogen metabolism. The developed analytical methods were successfully employed to compare the biological transformation of 17β-estradiol (E2), with and without the BODIPY fluorescent tag. Through measuring the complete degradation of E2 and the transformation of BODIPY-estradiol to BODIPY-estrone in the presence of a co-substrate, we found that BODIPY-labeled estrogens are biologically viable surrogates for investigating biodegradation in environmental bacteria.

The resulting mixture was then stirred at rt for 2h, and was then concentrated in vacuo. The crude residue was dissolved in CH2Cl2 (10 mL), and washed sequentially with 1M HCl (10 mL), H2O (10 mL) and brine (10 mL). The organic layer was then dried (Na2SO4), and concentrated in vacuo to afford the estradiol product X7 (86 mg, 86%) as a colourless oil, which required no further purification.

3-O-Propargyl-(16-O,17-O-dimethylacetyl)estriol, X8.
A suspension of estriol (100 mg, 0.3 mmol) in a mixture of THF (2 mL) and acetone (2 mL) was treated with p-TsOH (3 mg, 0.02 mmol), and the reaction was cooled to 0 °C before being treated with 2methoxypropene (67 µL, 0.7 mmol). After 2h, a further portion of 2-methoxypropene (67 µL, 0.7 mmol) was added, causing the suspension to become a yellow solution. After stirring for a further 2 h at rt, the reaction mixture was neutralised with enough drops of Et3N to turn the solution a pale yellow colour. The solution was dried (Na2SO4), and concentrated in vacuo to afford a crude yellow oil. Purification of the Page S7 crude residue by flash column chromatography (5-10% EtOAc/petroleum ether) afforded the ketalprotected product (90 mg, 79%) as a semi-crude compound. The semi-crude material (90 mg, 0.3 mmol) was dissolved in DMF (4 mL) and treated with K2CO3 (189 mg, 1.4 mmol). Propargyl bromide (153 µL, 1.4 mmol, 80% in toluene) was then added and the resulting reaction mixture was heated at 70 °C for 16h.
The reaction was then cooled down to rt, and diluted with EtOAc (25 mL) before being washed with aq.

II. Standards Preparation
Individual stock solutions of each estrogen were prepared by weighing out the solid material (fine, white crystals) and then dissolving the weighted material in methanol to a concentration of 1 mg/mL. Stock solutions of each BODIPY-tagged estrogen were prepared similarly by weighing out the solid material (fine, red-orange crystals) and then dissolving the weighted material in methanol to a concentration of 1 mg/mL. Individual stock solutions were stored in the dark at -20°C.
On the first day of method evaluation, four sub-stock solutions were prepared by diluting the 1 mg/mL stock solutions in acetonitrile. The first sub-stock consisted of E1 and E2 at 4 μg/mL each, and the second sub-stock contained E3 at 8 μg/mL. The third sub-stock contained BODIPY-E1 and BODIPY-E2 at 9 μg/mL, and the final sub-stock contained BODIPY-E3 also at 9 μg/mL. Sub-stock solutions were stored in the dark at -20°C in amber vials for the total duration of experiments (5 days). The calibration standards and quality controls (QCs) used for system suitability and the method evaluations were prepared from the sub-stock solutions fresh for each batch. The concentrations of each standard and QC are detailed in Table   S1. Page S12  Page S13

a. Linearity
Linearity for each batch was determined using unweighted linear regression of the concentration (x) versus the response (i.e. peak area) ratio of analyte to internal or surrogate standard (y). The coefficient of determination (R 2 ) of the calculated linear regression equation where a is slope and b is the intercept) was used to evaluate the linearity of the method. Additionally, the percent error (Equation S1, Figure S2)

b. Precision
Precision was determined by the percent relative standard deviation (%RSD) of a set of replicate injections. Repeatability was evaluated by the percent relative standard deviation (%RSD) for the initial six repeat injections at the start of the first batch (Injections #1-6). Page S15

c. Accuracy
Accuracy was determined by the percent error (Equation S1) of the three quality controls measured in duplicate over three separate batches, as recommended by the Bioanalytical Method Validation Guidance for Industry. 3 Here, xc and xi are the calculated and true concentrations of the QC sample, respectively. Additionally, the percent recovery (Equation

S2
) was used as an additional measure of trueness as recommended by the ICH Guidelines and Eurachem Guide to Method Validation: 4,5 % Recovery = 100% × . A breakdown of the percent error and recovery for each QC level are detailed in Tables S3 for   E1 and S4 for E2.  Page S17

d. Instrument Limits of Detection and Quantitation
The instrument limits of detection (LOD) and quantitation (LOQ) were calculated for each calibration curve using Equation S3, where k is 3.3 for LOD and 10 for LOQ, sb is the standard error of the intercept, and S is the regression slope. This model is based on the ICH Guidelines for determining limits of detection and quantitation, which states that the standard deviation of the y-intercept may be used as representation for standard deviation of the response. 4 Because the estimates of the instrumental limits of detection and quantitation are based on the regression curves, these values were also determined for each individual batch.
Page S18